| Presentation | 2017-03-14 Search Capability of DPSO with Dynamically Varying Gain-Parameter Nobuaki Hashimoto, Masato Kaneko, Toshiya Iwai, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Discrete Particle Swarm Optimization(DPSO) is a metaheuristics that is improved to apply PSO to the discrete optimization problem. Although the update rule of both particle position and velocity for DPSO is formally represented by difference equations of motion of the particle, the dimensional component of the velocity is connected by a probability of the value that its corresponding component of the position vector takes. In this study, introducing gain parameter β in the sigmoid function to control the degree of uncertainty of the probability in the update rule, we numerically investigate the relation between β and the global search capability and whether time scheduling of β improves search performance. Results of our numerical simulation show as follows: (i) the global search capability increases with decreasing the value of β, (ii) in the case of time scheduling function of β, temporally increasing functions β(t) show the large search capability in comparison with decreasing functions, (iii) as compared between properties of search processes for the temporally constant β and the exponentially increasing downward convex function β(t), β(t) realizes search processes with good balance between the ability to search better solutions and the search velocity. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Particle Swarm Optimization / Discrete Particle Swarm Optimization / sigmoid function / time scheduling / search capability / knapsack problem |
| Paper # | NLP2016-106 |
| Date of Issue | 2017-03-07 (NLP) |
| Conference Information | |
| Committee | NLP |
|---|---|
| Conference Date | 2017/3/14(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nebuta Museum Warasse |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Hisato Fujisaka(Hiroshima City Univ.) |
| Vice Chair | Masaharu Adachi(Tokyo Denki Univ.) |
| Secretary | Masaharu Adachi(Konan Univ.) |
| Assistant | Hiroyuki Asahara(Okayama Univ. of Science) / Toshihiro Tachibana(Shonan Inst. of Tech.) |
| Paper Information | |
| Registration To | Technical Committee on Nonlinear Problems |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Search Capability of DPSO with Dynamically Varying Gain-Parameter |
| Sub Title (in English) | |
| Keyword(1) | Particle Swarm Optimization |
| Keyword(2) | Discrete Particle Swarm Optimization |
| Keyword(3) | sigmoid function |
| Keyword(4) | time scheduling |
| Keyword(5) | search capability |
| Keyword(6) | knapsack problem |
| 1st Author's Name | Nobuaki Hashimoto |
| 1st Author's Affiliation | Nihon University(Nihon Univ.) |
| 2nd Author's Name | Masato Kaneko |
| 2nd Author's Affiliation | Nihon University(Nihon Univ.) |
| 3rd Author's Name | Toshiya Iwai |
| 3rd Author's Affiliation | Nihon University(Nihon Univ.) |
| Date | 2017-03-14 |
| Paper # | NLP2016-106 |
| Volume (vol) | vol.116 |
| Number (no) | NLP-523 |
| Page | pp.pp.1-6(NLP), |
| #Pages | 6 |
| Date of Issue | 2017-03-07 (NLP) |